Schneider, Thomas ; Suresh, Ajith ; Yalame, Hossein (2023)
Comments on “Privacy-Enhanced Federated Learning Against Poisoning Adversaries”.
In: IEEE Transactions on Information Forensics and Security, 18
doi: 10.1109/TIFS.2023.3238544
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Liu et al. (2021) recently proposed a privacy-enhanced framework named PEFL to efficiently detect poisoning behaviours in Federated Learning (FL) using homomorphic encryption. In this article, we show that PEFL does not preserve privacy. In particular, we illustrate that PEFL reveals the entire gradient vector of all users in clear to one of the participating entities, thereby violating privacy. Furthermore, we clearly show that an immediate fix for this issue is still insufficient to achieve privacy by pointing out multiple flaws in the proposed system.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2023 |
Autor(en): | Schneider, Thomas ; Suresh, Ajith ; Yalame, Hossein |
Art des Eintrags: | Bibliographie |
Titel: | Comments on “Privacy-Enhanced Federated Learning Against Poisoning Adversaries” |
Sprache: | Englisch |
Publikationsjahr: | 20 Januar 2023 |
Verlag: | IEEE |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Transactions on Information Forensics and Security |
Jahrgang/Volume einer Zeitschrift: | 18 |
DOI: | 10.1109/TIFS.2023.3238544 |
URL / URN: | https://ieeexplore.ieee.org/document/10023534 |
Kurzbeschreibung (Abstract): | Liu et al. (2021) recently proposed a privacy-enhanced framework named PEFL to efficiently detect poisoning behaviours in Federated Learning (FL) using homomorphic encryption. In this article, we show that PEFL does not preserve privacy. In particular, we illustrate that PEFL reveals the entire gradient vector of all users in clear to one of the participating entities, thereby violating privacy. Furthermore, we clearly show that an immediate fix for this issue is still insufficient to achieve privacy by pointing out multiple flaws in the proposed system. |
Freie Schlagworte: | Engineering, E4, Cryptography and Privacy Engineering (ENCRYPTO), GRK Privacy&Trust for Mobile Users (Project A.1) |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Praktische Kryptographie und Privatheit DFG-Sonderforschungsbereiche (inkl. Transregio) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche Profilbereiche Profilbereiche > Cybersicherheit (CYSEC) DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1119: CROSSING – Kryptographiebasierte Sicherheitslösungen als Grundlage für Vertrauen in heutigen und zukünftigen IT-Systemen |
Hinterlegungsdatum: | 21 Mär 2023 10:07 |
Letzte Änderung: | 21 Mär 2023 10:07 |
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